P. R Anisha – författare

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models.It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models.It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0.Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical roboticsExplains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.

The book studies emerging and sustaining technologies for applications of Industry 5.0 to develop technological solutions to address numerous real-life challenges to solve sustainable development-related issues. It identifies limitations, pitfalls, and open research questions in industry 5.0, discusses real-time problems, and challenges with equivalent solutions with a focus on sustainable growth to develop, humanization and environmentally friendly intelligent system applications. It analyses applications enabled by Industry 5.0 such as healthcare, supply chain, smart framing, remote sensing, production in manufacturing, and cloud manufacturing. It also includes the difficulties and problems posed by the organization between robots and humans on the assembly line to maintain sustainability.Addresses key challenges in implementing intelligent systems in IoT-based applications, including issues ranging from cost and energy efficiency to availability and quality of serviceExplores the technologies to allow human-machine association and its impact on consumption and sustainabilityProvides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineeringExamines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in IndustryPresents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 eraThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology, especially for professionals and researchers interested in the technological side of sustainable development.

The book studies emerging and sustaining technologies for applications of Industry 5.0 to develop technological solutions to address numerous real-life challenges to solve sustainable development-related issues. It identifies limitations, pitfalls, and open research questions in industry 5.0, discusses real-time problems, and challenges with equivalent solutions with a focus on sustainable growth to develop, humanization and environmentally friendly intelligent system applications. It analyses applications enabled by Industry 5.0 such as healthcare, supply chain, smart framing, remote sensing, production in manufacturing, and cloud manufacturing. It also includes the difficulties and problems posed by the organization between robots and humans on the assembly line to maintain sustainability.Addresses key challenges in implementing intelligent systems in IoT-based applications, including issues ranging from cost and energy efficiency to availability and quality of serviceExplores the technologies to allow human-machine association and its impact on consumption and sustainabilityProvides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineeringExamines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in IndustryPresents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 eraThe text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology, especially for professionals and researchers interested in the technological side of sustainable development.

The text emphasizes the need for data pre-processing, classification and prediction, cluster analysis, mining multimedia, and advanced machine learning techniques for scientific programming in Industry 5.0.Addresses how the convergence of intelligent systems and 5G wireless systems will solve industrial problems such as autonomous robots, and self-driving carsHighlights the methods of smart things in collaborative autonomous fleets and platforms for integrating applications across different business and industry domainsDiscusses important topics such as the Internet of robotic things, cloud robotics, and cognitive architecture for cyber-physical roboticsExplains image compression, and advanced machine learning techniques for scientific programming in Industry 5.0Presents a detailed discussion of smart manufacturing techniques, industrial Internet of things, and supply chain management in Industry 5.0The text is primarily written for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, electrical engineering, production engineering, and mechanical engineering.